{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "73bd968b-d970-4a05-94ef-4e7abf990827",
   "metadata": {},
   "source": [
    "Chapter 12\n",
    "\n",
    "# 对数坐标\n",
    "Book_3《数学要素》 | 鸢尾花书：从加减乘除到机器学习 (第二版)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1f3484b-4738-4c5a-88e0-75c6b747c606",
   "metadata": {},
   "source": [
    "这段代码绘制了三种函数 $$f(x) = 10^x$$、$$f(x) = x$$ 和 $$f(x) = \\log(x)$$ 的曲线，并在三种不同的坐标尺度下展示了它们的变化特性。具体来说：\n",
    "\n",
    "1. **x 轴对数坐标**：在这幅图中，代码使用了 x 轴的对数刻度，以展示不同增速的函数在对数坐标下的表现。$$f(x) = 10^x$$ 为指数函数，增长极快，而 $$f(x) = x$$ 为线性增长，$$f(x) = \\log(x)$$ 则表示对数增长，速度较慢。\n",
    "\n",
    "2. **y 轴对数坐标**：在第二幅图中，代码使用 y 轴的对数刻度来展示三种函数在不同增长模式下的相对变化。指数函数 $$f(x) = 10^x$$ 呈现出线性增长的趋势，因为其在对数 y 轴下变为直线，而线性函数 $$f(x) = x$$ 则表现出放缓趋势，对数函数 $$f(x) = \\log(x)$$ 更为缓慢。\n",
    "\n",
    "3. **双对数坐标**：在第三幅图中，x 轴和 y 轴都采用对数刻度，进一步展示了这三种函数在双对数尺度下的相对变化。$$f(x) = 10^x$$ 表现出非常快的增长，$$f(x) = x$$ 在对数尺度下则呈现为直线，而 $$f(x) = \\log(x)$$ 进一步放缓，变化相对较小。\n",
    "\n",
    "这些图形通过改变坐标尺度，从多个角度展示了不同增长速度的函数（指数、线性和对数）在不同坐标尺度下的相对表现，从而便于理解它们的增长趋势和相对变化。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccc52f5e-f456-462c-a8f0-055f56695df3",
   "metadata": {},
   "source": [
    "## 导入包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b36febc4-ecee-42b9-ad0a-d8cef7b52a36",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np  # 导入numpy库，用于数值计算\n",
    "import matplotlib.pyplot as plt  # 导入matplotlib库，用于绘图\n",
    "\n",
    "p = plt.rcParams  # 获取默认绘图参数\n",
    "p[\"font.sans-serif\"] = [\"Roboto\"]  # 设置无衬线字体为 Roboto\n",
    "p[\"font.weight\"] = \"light\"  # 设置字体粗细为 light\n",
    "p[\"ytick.minor.visible\"] = True  # 显示 y 轴的小刻度\n",
    "p[\"xtick.minor.visible\"] = True  # 显示 x 轴的小刻度\n",
    "p[\"axes.grid\"] = True  # 启用坐标轴网格\n",
    "p[\"grid.color\"] = \"0.5\"  # 设置网格颜色为灰色\n",
    "p[\"grid.linewidth\"] = 0.5  # 设置网格线宽度"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5dae73db-d5a8-4292-9c45-6e76245806b0",
   "metadata": {},
   "source": [
    "## 定义x和y的取值范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2e9dad80-4c55-4cbb-8cd4-a8c3c3c565eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = np.linspace(-1, 10, 100)  # 定义x轴范围从0.1到10\n",
    "x = np.linspace(0.001, 10, 100)  # 定义x轴范围从0.1到1000"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2504b04b-4cdd-406e-9615-ca9dca0a2c2a",
   "metadata": {},
   "source": [
    "## 线性坐标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6b111918-4af8-48e9-a340-52431ab4aed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1 = 10**x1  # 计算f1 = 10^x1\n",
    "f2 = x1  # 计算f2 = x1\n",
    "f3 = np.log(x)  # 计算f3 = log(x)\n",
    "\n",
    "fig, ax = plt.subplots()  # 创建图形和坐标轴\n",
    "plt.plot(x1, f1, color='r')  # 绘制f1曲线，颜色为红色\n",
    "plt.plot(x1, f2, color='k')  # 绘制f2曲线，颜色为黑色\n",
    "plt.plot(x, f3, color='b')  # 绘制f3曲线，颜色为蓝色\n",
    "plt.xlim((-1, 10))  # 设置x轴范围\n",
    "plt.ylim((-1, 10))  # 设置y轴范围\n",
    "# 配置网格线\n",
    "ax.grid(which='major', linestyle='-', linewidth=0.5, color='0.5')  # major网格线\n",
    "ax.grid(which='minor', linestyle='-', linewidth=0.3, color='0.8')  # minor网格线\n",
    "plt.tight_layout()  # 自动调整布局\n",
    "ax.set_box_aspect(1)  # 设置图形比例"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "633b4cc7-255b-43a3-9f87-3ae1ad9148bc",
   "metadata": {},
   "source": [
    "## x轴对数坐标绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1768af2b-e7d7-412c-89f0-941117496998",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = np.linspace(0.1, 10, 100)  # 定义x轴范围从0.1到10\n",
    "x = np.linspace(0.1, 1000, 100)  # 定义x轴范围从0.1到1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "af5bad1f-e851-4d7a-98fe-557a90879c09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1 = 10**x1  # 计算f1 = 10^x1\n",
    "f2 = x1  # 计算f2 = x1\n",
    "f3 = np.log(x)  # 计算f3 = log(x)\n",
    "\n",
    "fig, ax = plt.subplots()  # 创建图形和坐标轴\n",
    "plt.plot(x1, f1, color='r')  # 绘制f1曲线，颜色为红色\n",
    "plt.plot(x1, f2, color='k')  # 绘制f2曲线，颜色为黑色\n",
    "plt.plot(x, f3, color='b')  # 绘制f3曲线，颜色为蓝色\n",
    "\n",
    "plt.xscale(\"log\")  # 设置x轴为对数坐标\n",
    "plt.ylim((-0.5, 10))  # 设置y轴范围\n",
    "# 配置网格线\n",
    "ax.grid(which='major', linestyle='-', linewidth=0.5, color='0.5')  # major网格线\n",
    "ax.grid(which='minor', linestyle='-', linewidth=0.3, color='0.8')  # minor网格线\n",
    "plt.tight_layout()  # 自动调整布局\n",
    "ax.set_box_aspect(1)  # 设置图形比例"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "109ec9ce-042c-492c-843e-c2fc625a89d5",
   "metadata": {},
   "source": [
    "## y轴对数坐标绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2011aaed-7944-4b7c-b8ba-d6cf1bb1697f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1 = 10**x1  # 计算f1 = 10^x1\n",
    "f2 = x1  # 计算f2 = x1\n",
    "f3 = np.log(x1)  # 计算f3 = log(x1)\n",
    "\n",
    "fig, ax = plt.subplots()  # 创建图形和坐标轴\n",
    "plt.plot(x1, f1, color='r')  # 绘制f1曲线，颜色为红色\n",
    "plt.plot(x1, f2, color='k')  # 绘制f2曲线，颜色为黑色\n",
    "plt.plot(x1, f3, color='b')  # 绘制f3曲线，颜色为蓝色\n",
    "\n",
    "plt.yscale(\"log\")  # 设置y轴为对数坐标\n",
    "plt.ylim((0.1, 1000))  # 设置y轴范围\n",
    "# 配置网格线\n",
    "ax.grid(which='major', linestyle='-', linewidth=0.5, color='0.5')  # major网格线\n",
    "ax.grid(which='minor', linestyle='-', linewidth=0.3, color='0.8')  # minor网格线\n",
    "plt.tight_layout()  # 自动调整布局\n",
    "ax.set_box_aspect(1)  # 设置图形比例"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5310b129-cbc0-42f5-9ff6-0cbc45e2a47c",
   "metadata": {},
   "source": [
    "## x轴和y轴均为对数坐标绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "03008db9-a4f9-4754-82e8-eba24355121f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_log_1 = np.logspace(np.log10(0.1), np.log10(3), num=100, endpoint=True, base=10.0)  # 定义对数间隔的x值\n",
    "x_log_2 = np.logspace(np.log10(0.1), np.log10(1000), num=100, endpoint=True, base=10.0)  # 定义对数间隔的x值\n",
    "x_log_3 = np.logspace(np.log10(1), np.log10(1000), num=100, endpoint=True, base=10.0)  # 定义对数间隔的x值\n",
    "\n",
    "f1 = 10**x_log_1  # 计算f1 = 10^x_log_1\n",
    "f2 = x_log_2  # 计算f2 = x_log_2\n",
    "f3 = np.log(x_log_3)  # 计算f3 = log(x_log_3)\n",
    "\n",
    "fig, ax = plt.subplots()  # 创建图形和坐标轴\n",
    "plt.plot(x_log_1, f1, color='r')  # 绘制f1曲线，颜色为红色\n",
    "plt.plot(x_log_2, f2, color='k')  # 绘制f2曲线，颜色为黑色\n",
    "plt.plot(x_log_3, f3, color='b')  # 绘制f3曲线，颜色为蓝色\n",
    "\n",
    "plt.yscale(\"log\")  # 设置y轴为对数坐标\n",
    "plt.xscale(\"log\")  # 设置x轴为对数坐标\n",
    "plt.ylim((0.1, 1000))  # 设置y轴范围\n",
    "plt.xlim((0.1, 1000))  # 设置x轴范围\n",
    "# 配置网格线\n",
    "ax.grid(which='major', linestyle='-', linewidth=0.5, color='0.5')  # major网格线\n",
    "ax.grid(which='minor', linestyle='-', linewidth=0.3, color='0.8')  # minor网格线\n",
    "plt.tight_layout()  # 自动调整布局\n",
    "ax.set_box_aspect(1)  # 设置图形比例"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
